Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “AVHRR”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 145 records · Page 8

Comparison of sea ice parameters retrieved from passive microwave (SSM/I), Landsat MSS and AVHRR imagery

Ice concentrations derived from passive microwave data from the Special Sensing Microwave Imager (SSM/I), the Landsat MSS, and the AVHRR are compared for the validation of SSM/I-derived sea-ice products. Case studies with data from the Beaufort, Bering, East Greenland, and Weddell Seas are conducted to evaluate the performance of the NASA Team SSM/I algorithm under various sea-ice conditions. The results show that SSM/I ice concentrations are accurate with a mean error of 15 percent using globally derived tie points.

Schweiger, Axel J.↗

Representation of vegetation by continental data sets derived from NOAA-AVHRR data

Images of the normalized difference vegetation index (NDVI) are examined with specific attention given to the effect of spatial scales on the understanding of surface phenomena. A scale variance analysis is conducted on NDVI annual and seasonal images of Africa taken from 1987 NOAA-AVHRR data at spatial scales ranging from 8-512 km. The scales at which spatial variation takes place are determined and the relative magnitude of the variations are considered. Substantial differences are demonstrated, notably an increase in spatial variation with coarsening spatial resolution. Different responses in scale variance as a function of spatial resolution are noted in an analysis of maximum value composites for February and September; the difference is most marked in areas with very seasonal vegetation. The spatial variation at different scales is attributed to different factors, and methods involving the averaging of areas of transition and surface heterogeneity can oversimplify surface conditions. The spatial characteristics and the temporal variability of areas should be considered to accurately apply satellite data to global models.

Justice, C. O.↗

The effect of water vapour on the normalized difference vegetation index derived for the Sahelian region from NOAA AVHRR data

The near-infrared channel of the NOAA advanced very high resolution radiometer (AVHRR) contains a water vapor absorption band that affects the determination of the normalized difference vegetation index (NDVI). Daily and seasonal variations in atmospheric water vapor within the Sahel are shown to affect the use of the NDVI for the estimation of primary production. This water vapor effect is quantified for the Sahel by radiative transfer modeling and empirically using observations made in Mali in 1986.

Justice, Christopher O.↗

Atmospheric effects on NOAA AVHRR data over Sahelian regions

Variable atmospheric conditions have a significant impact on satellite monitoring of vegetation in the Sahelian zone of Africa. The effects of atmospheric O3, H2O, and aerosols on spectral, directional reflectances and derived measures, such as the normalized difference vegetation index are discussed using a sensitivity study. An atmospheric correction scheme is presented based on measurements of optical thicknesses from the ground and is applied to NOAA AVHRR data. The use of the reflectance of the ocean surface close to the terrestrial target to estimate atmospheric effects on terrestrial reflectance is also discussed.

Soufflet, V.↗

Synergism between NOAA-AVHRR and Meteosat data for studying vegetation development in semi-arid West Africa

Rainfall estimates, based on cold cloud duration estimated from Meteosat data, are compared with vegetation development depicted by data of the normalized difference vegetation index (NDVI) from the NOAA AVHRR for part of the Sahel. Decadal data from the 1985 and 1986 growing seasons are examined to determine the synergism of the datasets for rangeland monitoring. There is a general correspondence between the two datasets with a marked lag between rainfall and NDVI of between 10 and 20 days. This time lag is particularly noticeable at the beginning of the rainy season and in the more northern areas where rainfall is the limiting factor for growth. Principal component analysis was used to examine deviations from the general relationship between rainfall and the NDVI. Areas of low NDVI values for a given input of rainfall were identified: at a regional scale, they give an indication o areas of low production potential and possible degradation of ecosystems.

Justice, C. O.↗

An analysis of cloud property retrieval using HIRS-2 and AVHRR radiometric data

The principal advantage of the HIRS cloud height retrieval is to provide an unbiased estimate of cloud height for optically thin, high cloud. This capability is employed to examine the relationship of cirrus visible reflectance to thermal IR emittance. By combining data from the HIRS-2 and AVHRR instruments on the NOAA operational satellites the proposed method attempts to improve the ability of existing satellite radiometers to recover information on middle-level and high-level clouds. This combination of data sets leads to an improved cloud recovery algorithm for the detection and analysis of cirrus clouds.

Baum, Bryan A.↗

Cloud classification in polar regions using AVHRR textural and spectral signatures

Arctic clouds and ice-covered surfaces are classified on the basis of textural and spectral features obtained with AVHRR 1.1-km spatial resolution imagery over the Beaufort Sea during May-October, 1989. Scenes were acquired about every 5 days, for a total of 38 cases. A list comprising 20 arctic-surface and cloud classes is compiled using spectral measures defined by Garand (1988).

Welch, R. M.↗

Radiometric calibration and monitoring of NOAA AVHRR data for ISCCP

The methodology developed to monitor the radiometric calibration of NOAA AVHRR data and to normalize succeeding polar orbiters for the International Satellite Cloud Project (ISCCP) is described. Results are given for NOAA-7, -8, and -9 Channel 1 (visible) data. The successful normalization of NOAA-8, and -9, to NOAA-7 permits the ISCCP calibration standard to be maintained over time. A correction for the degradation of NOAA-9 data and an absolute calibration for the entire ISCCP dataset are presented.

Brest, Christopher L.↗

Regional surface fluxes from satellite-derived surface temperatures (AVHRR) and radiosonde profiles

Radiometric surface temperatures, derived from measurements by the AVHRR instrument aboard the NOAA-9 and the NOAA-11 polar orbiting satellites, were used in combination with wind velocity and temperature profiles measured by radiosondes, to calculate surface fluxes of sensible heat. The measurements were made during FIFE, the First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment, in a hilly tall grass prairie area of northeastern Kansas. The method of calculation was based on turbulent similarity formulations for the atmospheric boundary layer. Good agreement (r = 0.7) was obtained with reference values of sensible heat flux, taken as arithmetric means of measurements with the Bowen ratio method at six ground stations. The values of evaporation (latent heat fluxes), derived from these sensible heat fluxes by means of the energy budget, were also in good agreement (r = 0.94) with the corresponding reference values from the ground stations.

Brutsaert, Wilfried↗

Remote sensing cloud properties from combined AVHRR HIRS/2 and ERBE observations

The paper describes a method for determining cloud parameters from the combined remote sensing measurements of the NOAA AVHRR and the High-Resolution Infrared Radiometer Sounder (HIRS-2). The method was implemented on a set of observations primarily limited to the tropical eastern Pacific. Examples of applications of this data set are presented.

Ackerman, Steven A.↗

Cloud-property retrieval using merged HIRS and AVHRR data

A technique is developed that uses a multispectral, multiresolution method to improve the overall retrieval of mid- to high-level cloud properties by combining HIRS sounding channel data with higher spatial resolution AVHRR radiometric data collocated with the HIRS footprint. Cirrus cloud radiative and physical properties are determined using satellite data, surface-based measurements provided by rawinsondes and lidar, and aircraft-based lidar data collected during the First International Satellite Cloud Climatology Program Regional Experiment in Wisconsin during the months of October and November 1986. HIRS cloud-height retrievals are compared to ground-based lidar and aircraft lidar when possible. Retrieved cloud heights are found to have close agreement with lidar for thin cloud, but are higher than lidar for optically thick cloud. The results of the reflectance-emittance relationships derived are compared to theoretical scattering model results for both water-droplet spheres and randomly oriented hexagonal ice crystals. It is found that the assumption of 10-micron water droplets is inadequate to describe the reflectance-emittance relationship for the ice clouds seen here. Use of this assumption would lead to lower cloud heights using the ISCCP approach. The theoretical results show that use of hexagonal ice crystal phase functions could lead to much improved results for cloud retrieval algorithms using a bispectral approach.

Baum, Bryan A.↗

Estimation of emittances and surface temperatures from AVHRR data

An approach to the estimation of surface temperatures and emissivities using AVHRR (Advanced Very High Resolution Radiometer) data acquired near noon is presented. Thermal data in channels 3, 4, and 5 were used to estimate the reflective component in 3. For three water bodies in Oregon the average emittances found for channels 3 and 4 were 0.979 and 0.991, respectively. Also studied were agricultural sites and forests, comprising both primary (PF) and secondary (SF) types. For the agricultural sites, the average emittances were 0.919 and 0.943 for channels 3 and 4. For the PF and SF the results were 0.976 and 0.983 for channel 3 and 0.988 and 0.995 for channel 4.

Schutt, John B.↗

Arctic ice surface temperature retrieval from AVHRR thermal channels

The relationship between AVHRR thermal radiances and the surface (skin) temperature of Arctic snow-covered sea ice is examined through forward calculations of the radiative transfer equation, providing an ice/snow surface temperature retrieval algorithm for the central Arctic Basin. Temperature and humidity profiles with cloud observations collected on an ice island during 1986-1987 are used. Coefficients that correct for atmospheric attenuation are given for three Arctic clear sky 'seasons', as defined through statistical analysis of the daily profiles, for the NOAA 7, 9, and 11 satellites. Modeled directional snow emissivities, different in the two split-window (11 and 12 micron) channels, are used. While the sensor scan angle is included explicitly in the correction equation, its effect in the dry Arctic atmosphere is small, generally less than 0.1 K. Using the split-window channels and scan angle, the rms error in the estimated ice surface temperature is less than 0.1 K in all seasons. Inclusion channel 3(3.7 microns) during the winter decreases the rms error by less than 0.003

Key, J.↗

Polar cloud and surface classification using AVHRR imagery - An intercomparison of methods

Six Advanced Very High-Resolution Radiometer local area coverage (AVHRR LAC) arctic scenes are classified into ten classes. Three different classifiers are examined: (1) the traditional stepwise discriminant analysis (SDA) method; (2) the feed-forward back-propagation (FFBP) neural network; and (3) the probabilistic neural network (PNN). More than 200 spectral and textural measures are computed. These are reduced to 20 features using sequential forward selection. Theoretical accuracy of the classifiers is determined using the bootstrap approach. Overall accuracy is 85.6 percent, 87.6 percent, and 87.0 percent for the SDA, FFBP, and PNN classifiers, respectively, with standard deviations of approximately 1 percent.

Welch, R. M.↗

Aerosol retrieval over land from AVHRR data - Application for atmospheric correction

Two retrieval mechanisms previously developed for Landsat are presently modified for the NOAA satellites' AVHRR. While the first of these methods retrieves aerosols on the basis of atmospheric effects on the path radiance, the second employs the change in contrast for several scenes to ascertain the change in optical thickness between the scenes. The two methods are presently discussed with reference to other methods, as well as with a view to their implications for global-scale aerosol monitoring and atmospheric correction.

Holben, Brent N.↗

Analysis of AVHRR, CZCS and historical in situ data off the Oregon Coast

The original scientific objectives of this grant were to: (1) characterize the seasonal cycles and interannual variability for phytoplankton concentrations and sea surface temperature (SST) in the California Current using satellite data; and (2) to explore the spatial and temporal relationship between these variables and surface wind forcing. An additional methodological objective was to develop statistical methods for forming mean fields, which minimize the effects of random data gaps and errors in the irregularly sampled CZCS (Coastal Zone Color Scanner) and AVHRR (Advanced Very High Resolution Radiometer) satellite data. A final task was to evaluate the level of uncertainty in the wind fields used for the statistical analysis. Funding in the first year included part of the cost of an image processing system to enable this and other projects to process and analyze satellite data. This report consists of summaries of the major projects carried out with all or partial support from this grant. The appendices include a list of papers and professional presentations supported by the grant, as well as reprints of the major papers and reports.

Strub, P. Ted↗

A comprehensive comparison between skin and multi-channel sea surface temperatures as derived from AVHRR

Global maps of Satellite Measured Surface Skin Temperature (SMSST), MultiChannel Sea Surface Temperature (MCSST) and Cross Product Sea Surface Temperature (CPSSR) are computed from imagery of the Advanced Very High Resolution Radiometer (AVHRR) for five fortnights in 1984/85. They demonstrate systematic latitudinal variations and regional extremes of the differences with greatest root mean square values of 0.7K between MCSST and SMSST found at low latitudes. Mean differences range from 0.1K between CPSST and SMSST to 0.45K between MCSST and SMSST. A part of the differences might be attributed to the skin cooling at the sea surface. A parameterization of the bulk skin temperature difference is derived from in situ field measurements. This can be used to find a relation between satellite measured bulk and skin temperatures.

Schluessel, Peter↗

Calibration of the AVHRR visible and near-IR bands by atmospheric scattering, ocean glint and desert reflection

A method for calibrating satellite sensors (such as the AVHRR visible and NIR bands) is proposed by which the sensors are calibrated using well-known physical characteristics of the atmosphere, ocean, and deserts, as well as the digital satellite imagery. The approach, independent of ground support, used the following three phenomena: molecular scattering over the ocean for absolute visible band calibration; ocean glint, to transfer the calibration from the visible band to the NIR band; and desert reflectance to monitor, independently, the stability of the visible and NIR bands. The method was applied to NOAA-7, -9, and -11 sensors. The results of the ocean and the desert calibration methods were found to differ in the brightness range and the spectral response of the radiance source (molecular scattering over the ocean versus the desert reflectance).

Kaufman, Y. J.↗